1. Field of the Invention
This invention relates to high dynamic range (HDR) imaging, and in particular, it relates to removal of ghost artifact during HDR image creation.
2. Description of Related Art
High dynamic range (HDR) imaging is a technique used in image processing and digital photography to handle sources that have extremely large ranges of brightness (light intensity). For example, an outdoor scene in daylight may include blue sky and sunlit objects as well as objects in shadows; a night scene may include neon lights and brightly lit objects as well as poorly lit objects; an indoor scene may include bright windows as well as darker areas, etc. These scenes pose a challenge for imaging devices such as digital cameras; the dynamic range of currently available digital cameras often cannot adequately image such scenes. If the exposure level is adequate for capturing details of darker areas of the scene, the brighter areas will often be overexposed with details lost; conversely, if the exposure level is adequate for capturing details of brighter areas of the scene, the darker areas will often be underexposed with details lost.
HDR imaging techniques deal with this problem by taking multiple images of the same scene at various exposure levels, and then digitally merging the multiple images to create an HDR image that contains information from the multiple original images, so that details in both brighter and darker areas are adequately expressed in the HDR image. Methods for creating an HDR image from multiple original images are generally known. The original images are sometimes referred to as low-dynamic range (LDR) images (although it should be noted that this term does not mean that these images have low dynamic range).
During HDR image creation, ghosting artifacts can appear when object have moved, appeared or disappeared in between the shooting of the different original images. For example, during the shooting of three images, if a person walks into the scene only in the third image, then the HDR image created from the three images will have a semi-transparent figure of the person over the scene (“ghost”).
Methods have been proposed to identify such ghost-inducing objects within the multiple images, so that the images can be processed to reduce or eliminate ghosting effects in the resulting HDR image. Some of these techniques are described in a survey paper, A. Srikantha and D. Sidibé, Ghost Detection and Removal for High Dynamic Range Images: Recent Advances, Signal Processing: image Communications, 27(6), pp. 650-662, 2012.
Median threshold bitmap (MTB) has been demonstrated to be effective in detecting translation shifts among the original low dynamic range (LDR) images used to generate HDR images. Translation shifts refer to the shift in camera position during the taking of the multiple LDR images and the resulting shift in the scene. An image alignment method using MTB is described in Greg Ward, “Fast, Robust Image Registration for Compositing High Dynamic Range Photographs from Handheld Exposures,” Journal of Graphics Tools, Vol. 8 (2), pp. 17-30, 2003 (“Ward 2003”). The MTB method can also be used for ghost detection, as shown in F. Pece and J. Kautz, “Bitmap Movement Detection: HDR for Dynamic Scenes,” in Proceedings of Visual Media Production (CVMP), 2010, pp. 1-8 (“Pece and Kautz 2010”).